{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T04:28:25Z","timestamp":1743049705354,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":17,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819982950"},{"type":"electronic","value":"9789819982967"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-981-99-8296-7_9","type":"book-chapter","created":{"date-parts":[[2023,11,17]],"date-time":"2023-11-17T00:04:14Z","timestamp":1700179454000},"page":"118-131","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Efficient Mining of Top-K Cross-Level High Utility Itemsets"],"prefix":"10.1007","author":[{"given":"Nguyen Tuan","family":"Truong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nguyen Khac","family":"Tue","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nguyen Duc","family":"Chinh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Le Dinh","family":"Huynh","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vu Thu","family":"Diep","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Phan Duy","family":"Hung","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,11,17]]},"reference":[{"key":"9_CR1","unstructured":"Agrawal, R., Srikant, R.: Fast algorithms for mining association rules in large databases. In: Proceedings of the 20th International Conference on Very Large Data Bases, San Francisco, pp. 487\u2013499 (1994)"},{"issue":"2","key":"9_CR2","doi-asserted-by":"publisher","first-page":"207","DOI":"10.1145\/170036.170072","volume":"22","author":"R Agrawal","year":"1993","unstructured":"Agrawal, R., Imielinski, T., Swami, A.: Mining association rules between sets of items in large databases. ACM SIGMOD Rec. 22(2), 207\u2013216 (1993)","journal-title":"ACM SIGMOD Rec."},{"key":"9_CR3","series-title":"Studies in Big Data","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/978-3-030-04921-8_1","volume-title":"High-Utility Pattern Mining","author":"P Fournier-Viger","year":"2019","unstructured":"Fournier-Viger, P., Chun-Wei Lin, J., Truong-Chi, T., Nkambou, R.: A survey of high utility itemset mining. In: Fournier-Viger, P., Lin, J.-W., Nkambou, R., Vo, B., Tseng, V.S. (eds.) High-Utility Pattern Mining. SBD, vol. 51, pp. 1\u201345. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-04921-8_1"},{"key":"9_CR4","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1007\/978-3-319-08326-1_9","volume-title":"Foundations of Intelligent Systems","author":"P Fournier-Viger","year":"2014","unstructured":"Fournier-Viger, P., Cheng-Wei, Wu., Zida, S., Tseng, V.S.: FHM: faster high-utility itemset mining using estimated utility co-occurrence pruning. In: Andreasen, T., Christiansen, H., Cubero, J.-C., Ra\u015b, Z.W. (eds.) ISMIS 2014. LNCS (LNAI), vol. 8502, pp. 83\u201392. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-08326-1_9"},{"key":"9_CR5","doi-asserted-by":"crossref","unstructured":"Tseng, V.S., Wu, C.-W., Shie, B.-E., Yu, P.S.: UP-growth: an efficient algorithm for high utility itemset mining. In: Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 253\u2013262. Association for Computing Machinery, New York (2010)","DOI":"10.1145\/1835804.1835839"},{"key":"9_CR6","doi-asserted-by":"crossref","unstructured":"Liu, M., Qu, J.: Mining high utility itemsets without candidate generation. In: Proceedings of the 21st ACM International Conference on Information and Knowledge Management (CIKM 2012), pp. 55\u201364. Association for Computing Machinery, New York (2012)","DOI":"10.1145\/2396761.2396773"},{"key":"9_CR7","series-title":"Communications in Computer and Information Science","doi-asserted-by":"publisher","first-page":"224","DOI":"10.1007\/978-3-319-67162-8_22","volume-title":"New Trends in Databases and Information Systems","author":"L Cagliero","year":"2017","unstructured":"Cagliero, L., Chiusano, S., Garza, P., Ricupero, G.: Discovering high-utility itemsets at multiple abstraction levels. In: Kirikova, M., N\u00f8rv\u00e5g, K., Papadopoulos, G.A., Gamper, J., Wrembel, R., Darmont, J., Rizzi, S. (eds.) ADBIS 2017. CCIS, vol. 767, pp. 224\u2013234. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-67162-8_22"},{"key":"9_CR8","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"858","DOI":"10.1007\/978-3-030-55789-8_73","volume-title":"Trends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices","author":"P Fournier-Viger","year":"2020","unstructured":"Fournier-Viger, P., Wang, Y., Lin, J.-W., Luna, J.M., Ventura, S.: Mining cross-level high utility itemsets. In: Fujita, H., Fournier-Viger, P., Ali, M., Sasaki, J. (eds.) IEA\/AIE 2020. LNCS (LNAI), vol. 12144, pp. 858\u2013871. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-55789-8_73"},{"key":"9_CR9","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1016\/j.ins.2021.12.017","volume":"587","author":"NT Tung","year":"2022","unstructured":"Tung, N.T., Nguyen, L.T.T., Nguyen, T.D.D., Fourier-Viger, P., Nguyen, N.-T., Vo, B.: Efficient mining of cross-level high-utility itemsets in taxonomy quantitative databases. Inf. Sci. 587, 41\u201362 (2022). https:\/\/doi.org\/10.1016\/j.ins.2021.12.017","journal-title":"Inf. Sci."},{"key":"9_CR10","doi-asserted-by":"crossref","unstructured":"Wu, C.W., Shie, B.-E., Tseng, V.S., Yu, P.S.: Mining top-K high utility itemsets. In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2012 (2012)","DOI":"10.1145\/2339530.2339546"},{"issue":"1","key":"9_CR11","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1109\/TKDE.2015.2458860","volume":"28","author":"VS Tseng","year":"2016","unstructured":"Tseng, V.S., Wu, C.-W., Fournier-Viger, P., Yu, P.S.: Efficient algorithms for mining top-K high utility itemsets. IEEE Trans. Knowl. Data Eng. 28(1), 54\u201367 (2016)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"9_CR12","doi-asserted-by":"crossref","unstructured":"Nouioua, M., Wang, Y., Fournier-Viger, P., Lin, J.C.-W., Wu, J. M.-T.: TKC: mining top-K cross-level high utility itemsets. In: Proceedings of the International Conference on Data Mining Workshops, Sorrento, Italy, pp. 673\u2013682 (2020)","DOI":"10.1109\/ICDMW51313.2020.00095"},{"key":"9_CR13","series-title":"Advances in Intelligent Systems and Computing","doi-asserted-by":"publisher","first-page":"561","DOI":"10.1007\/978-981-33-4367-2_53","volume-title":"Emerging Technologies in Data Mining and Information Security","author":"NN Tram","year":"2021","unstructured":"Tram, N.N., Hung, P.D.: Analysing hot Facebook users posts\u2019 sentiment using deep learning. In: Hassanien, A.E., Bhattacharyya, S., Chakrabati, S., Bhattacharya, A., Dutta, S. (eds.) Emerging Technologies in Data Mining and Information Security. AISC, vol. 1300, pp. 561\u2013569. Springer, Singapore (2021). https:\/\/doi.org\/10.1007\/978-981-33-4367-2_53"},{"key":"9_CR14","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1007\/978-3-030-63007-2_20","volume-title":"Computational Collective Intelligence","author":"DH Phan","year":"2020","unstructured":"Phan, D.H., Do, Q.D.: Analysing effects of customer clustering for customer\u2019s account balance forecasting. In: Nguyen, N.T., Hoang, B.H., Huynh, C.P., Hwang, D., Trawi\u0144ski, B., Vossen, G. (eds.) ICCCI 2020. LNCS (LNAI), vol. 12496, pp. 255\u2013266. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-63007-2_20"},{"key":"9_CR15","series-title":"Lecture Notes in Networks and Systems","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1007\/978-981-19-2130-8_19","volume-title":"Communication and Intelligent Systems","author":"PN Hai","year":"2022","unstructured":"Hai, P.N., Hieu, H.T., Hung, P.D.: An empirical examination on forecasting VN30 short-term uptrend stocks using LSTM along with the Ichimoku cloud trading strategy. In: Sharma, H., Shrivastava, V., Kumari Bharti, K., Wang, L. (eds.) Communication and Intelligent Systems. LNNS, vol. 461, pp. 235\u2013244. Springer, Singapore (2022). https:\/\/doi.org\/10.1007\/978-981-19-2130-8_19"},{"key":"9_CR16","series-title":"Lecture Notes in Networks and Systems","doi-asserted-by":"publisher","first-page":"713","DOI":"10.1007\/978-981-19-9638-2_62","volume-title":"Information and Communication Technology for Competitive Strategies","author":"PD Hung","year":"2023","unstructured":"Hung, P.D., Son, D.N., Diep, V.T.: Building a recommendation system for travel location based on user check-ins on social network. In: Joshi, A., Mahmud, M., Ragel, R.G. (eds.) ICTCS 2022. LNNS, vol. 623, pp. 713\u2013724. Springer, Singapore (2023). https:\/\/doi.org\/10.1007\/978-981-19-9638-2_62"},{"key":"9_CR17","series-title":"Lecture Notes in Networks and Systems","doi-asserted-by":"publisher","first-page":"421","DOI":"10.1007\/978-981-19-0095-2_40","volume-title":"Information and Communication Technology for Competitive Strategies","author":"LH Nam","year":"2023","unstructured":"Nam, L.H., Hung, P.D., Vinh, B.T., Diep, V.T.: Practical fair queuing algorithm for message queue system. In: Joshi, A., Mahmud, M., Ragel, R.G. (eds.) ICTCS 2021. LNNS, vol. 400, pp. 421\u2013429. Springer, Singapore (2023). https:\/\/doi.org\/10.1007\/978-981-19-0095-2_40"}],"container-title":["Communications in Computer and Information Science","Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-99-8296-7_9","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,17]],"date-time":"2023-11-17T00:08:40Z","timestamp":1700179720000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-99-8296-7_9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9789819982950","9789819982967"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-981-99-8296-7_9","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"17 November 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"FDSE","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Future Data and Security Engineering","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Da Nang","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Vietnam","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 November 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 November 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"fdse2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/thefdse.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EquinOCS","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"135","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"38","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"8","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"28% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"6","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}